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From Sushrut Ikhar <sushrutikha...@gmail.com>
Subject Re: Spark Executor Lost issue
Date Wed, 28 Sep 2016 17:28:02 GMT
Can you add more details like are you using rdds/datasets/sql ..; are you
doing group by/ joins ; is your input splittable?
btw, you can pass the config the same way you are passing memryOverhead:
e.g.
--conf spark.default.parallelism=1000 or through spark-context in code

Regards,

Sushrut Ikhar
[image: https://]about.me/sushrutikhar
<https://about.me/sushrutikhar?promo=email_sig>


On Wed, Sep 28, 2016 at 7:30 PM, Aditya <aditya.calangutkar@augmentiq.co.in>
wrote:

> Hi All,
>
> Any updates on this?
>
> On Wednesday 28 September 2016 12:22 PM, Sushrut Ikhar wrote:
>
> Try with increasing the parallelism by repartitioning and also you may
> increase - spark.default.parallelism
> You can also try with decreasing num-executor cores.
> Basically, this happens when the executor is using quite large memory than
> it asked; and yarn kills the executor.
>
> Regards,
>
> Sushrut Ikhar
> [image: https://]about.me/sushrutikhar
> <https://about.me/sushrutikhar?promo=email_sig>
>
>
> On Wed, Sep 28, 2016 at 12:17 PM, Aditya <aditya.calangutkar@augmentiq.
> co.in> wrote:
>
>> I have a spark job which runs fine for small data. But when data
>> increases it gives executor lost error.My executor and driver memory are
>> set at its highest point. I have also tried increasing --conf
>> spark.yarn.executor.memoryOverhead=600 but still not able to fix the
>> problem. Is there any other solution to fix the problem?
>>
>>
>
>
>

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